Wireless communication control method, receiving station, and non-transitory storage medium

ABSTRACT

A wireless communication control method suppresses interference using an MMSE weight in an environment of wireless communication where the number of transmission stations transmitting a signal to a receiving station is larger than the number of reception antennas of the receiving station. The receiving station calculates power of an interference signal included in a signal received by the receiving station from the transmission stations the number of which is larger than the number of reception antennas, the interference signal corresponding to a part by which the number of transmission stations exceeds the number of reception antennas. The receiving station calculates the MMSE weight depending on the power of the interference signal, recalculates the power of the interference signal using the MMSE weight, and recalculates the MMSE weight depending on the recalculated power of the interference signal.

CROSS REFERENCE TO THE RELATED APPLICATION

This application claims the benefit of Japanese Patent Application No.2020-174176, filed on Oct. 15, 2020, which is hereby incorporated byreference herein in its entirety.

BACKGROUND 1. Technical Field

The present disclosure relates to a wireless communication controlmethod, a receiving station, and a non-transitory storage medium.

2. Description of the Related Art

There is a growing need to use a terminal connectable to a publicnetwork, such as the Internet, for control. Reduction in latency ofwireless communication accessing the public network has been demanded.Multiple-Input and multiple-output (MIMO) is used for wirelesscommunication. MIMO is a technology where a base station and terminalscommunicate in the same frequency band using multiple antennas for each.As for MIMO, a technology where multiple terminals engage incommunication simultaneously (in parallel) is called multi-user MIMO. Inrecent years, due to development of Internet of Things (IoT), rapidincrease of the number of wireless terminals used for IoT has beenpredicted, and there are growing concerns about uplink capacityshortage.

As for wireless communication, communication procedures calledconfigured grant (CG) are specified. According to the CG, the basestation preliminarily transmits, to terminal apparatuses, transmissionparameters that designate physical resources and the like usable fordata transmission. The base station notifies each terminal of startingpermission, finishing permission and the like of transmission of datausing the CG. The terminal can transmit data to the base station usingthe physical resource designated about the CG, with no negotiationbetween the terminal and the base station before data transmission. TheCG is expected as a technology of achieving low-latency communication.

In the environment where the CG is used, the base station does notcontrol data transmission timing of the terminal. Accordingly, thenumber N is limited that can be set such that the number of signalstransmitted from the terminals and reaching the base station at the sametiming (the number of transmission signals (the number of terminals): N)does not exceed the number of reception antennas (M) of the basestation. A state where the limitation on N is cancelled and the numberof reception antennas M exceeds the number of terminals N (N>M) iscalled overloaded MIMO. In an environment of overloaded MIMO, there is apossibility that the number of errors during desired signal duringdemodulation increases owing to effects of N-M interference signalsincapable of being cancelled even by diversity reception. The problem ofthe possibility of occurrence of errors during demodulation in theoverloaded MIMO is a problem that can also occur in an environment ofusing what is other than the CG with the limitation on N beingcancelled.

As measures against the overloaded MIMO, a signal separation process dueto maximum likelihood detection (MLD) or an MLD-applied technology hasbeen proposed. A method of using spatial filtering has also beenproposed.

For further information, see documents below.

-   [Non Patent Document 1] “NR Physical Layer Specifications in 5G,”    NTT DOCOMO Technical Journal Vol. 26 No. 3 (November 2018)-   [Non Patent Document 2] Suzuki, “Signal Transmission Characteristics    of Diversity Reception with Least-Squares Combining-Relationship    between Desired Signal Combining and Interference Cancelling-,”    Transactions of the Institute of Electronics, Information and    Communication Engineers, B-II Vol. J75-B-II, No. 8, pp. 524-534,    August, 1992-   [Non Patent Document 3] Hayakawa, Hayashi, and Kaneko, “A Reduced    Complexity Signal Detection Scheme for Overloaded MIMO Systems Using    Slab Decoding and Lattice Reduction,” Institute of Electronics,    Information and Communication Engineers Technical Report,    RCC2015-16, MICT2015-16, pp. 77-82, May, 2015-   [Non Patent Document 4] Higuchi, and Taoka, “Multi Antenna Wireless    Transfer Technology III Signal Separation Technology in MIMO    Multiplexing Method,” NTT DoCoMo Technical Journal Vol. 14 No. 1,    pp. 66-75, April, 2006

SUMMARY

There are, however, cases to which MLD is difficult to be applied; forexample, the cases include a system and the like that performequalization in a frequency area in single carrier transmission. Use ofspatial filtering is accompanied by a preprocess (special process),which complicates and tangles the processing.

The present disclosure has an object to provide a wireless communicationcontrol method, a receiving station, and a program that are capable ofsuppressing increase in error during decoding in overloaded MIMO.

The present disclosure is a wireless communication control methodsuppressing interference using a minimum mean square error (MMSE) weightin an environment of wireless communication where the number oftransmission stations transmitting a wireless signal to a receivingstation is larger than the number of reception antennas of the receivingstation. The wireless communication control method includes:calculating, by the receiving station, power of an interference signalincluded in a signal received by the receiving station from thetransmission stations the number of which is larger than the number ofreception antennas, the interference signal corresponding to a part bywhich the number of transmission stations exceeds the number ofreception antennas; calculating, by the receiving station, an MMSEweight depending on the power of the interference signal; andrecalculating, by the receiving station, the power of the interferencesignal using the MMSE weight depending on the power of the interferencesignal, and the MMSE weight depending on the recalculated power of theinterference signal.

The present disclosure may include the receiving station according tothe wireless communication control method described above, a programexecuted by a computer of the receiving station, and a non-transitorystorage medium to store the program.

According to the disclosed embodiment, increase in error during decodingin overloaded MIMO can be suppressed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating a configuration example of a wirelesscommunication system according to an embodiment;

FIG. 2 is a diagram illustrating a hardware configuration example of abase station;

FIG. 3 is a diagram illustrating a configuration example of a terminal;

FIG. 4 is a diagram illustrating a configuration example of the basestation;

FIG. 5 a diagram illustrating a case of diversity reception of a desiredsignal in an overloaded MIMO;

FIG. 6 a diagram illustrating a case of diversity reception of a desiredsignal in the overloaded MIMO;

FIG. 7 is a flowchart illustrating an example of a weight calculationprocess in MMSE diversity;

FIG. 8 illustrates definition of symbols used for weight calculation;

FIG. 9 is a table exemplifying a simulation condition;

FIG. 10 is a diagram illustrating a bit error rate difference dependingon presence or absence of weight calculation in the simulation; and

FIG. 11 is a diagram illustrating the bit error rate differencedepending on presence or absence of weight calculation in thesimulation.

DESCRIPTION OF THE EMBODIMENTS

A wireless communication control method according to the embodimentsuppresses interference using a minimum mean square error (MMSE) weightin an environment of wireless communication where the number oftransmission stations transmitting a wireless signal to a receivingstation is larger than the number of reception antennas of the receivingstation. The wireless communication control method includes thefollowing.

(1) The receiving station calculates power of an interference signalincluded in a signal received by the receiving station from thetransmission stations the number of which is larger than the number ofreception antennas, the interference signal corresponding to a part bywhich the number of transmission stations exceeds the number ofreception antennas.

(2) The receiving station calculates an MMSE weight depending on thepower of the interference signal.

(3) The receiving station recalculates the power of the interferencesignal using the MMSE weight depending on the power of the interferencesignal, and the MMSE weight depending on the recalculated power of theinterference signal.

The wireless communication control method according to the embodimentcalculates an MMSE weight (in consideration of power) depending on thepower of an interference signal corresponding to a part by which thenumber of transmission stations exceeds the number of receptionantennas. In other words, the wireless communication control methodaccording to the embodiment calculates the MMSE weight in considerationof power incapable of being suppressed (cancelled) by use of an MMSEweight obtained by a typical method of calculating the MMSE weight.Accordingly, interference can be suppressed more preferably than bysuppression through use of a typical MMSE weight, and can suppressincrease in error during demodulation.

Hereinafter, referring to the drawings, a wireless communication controlmethod of a wireless communication system, a receiving station includedin the wireless communication system, and a program executed in thereceiving station, according to the embodiment, are described. Theconfiguration in the embodiment is an example. There is no limitation bythe configuration of the embodiment. FIG. 1 a diagram illustrating aconfiguration example of a wireless communication system according to anembodiment.

In FIG. 1 , the wireless communication system includes a base station 1that includes multiple reception antennas, and multiple terminals 2-1,2-2, . . . , 2-N that wirelessly communicate with the base station 1.When the terminals 2-1 to 2-N are described without discrimination, theterminals are called “terminals 2”. The base station 1 is an example of“receiving station”. Each of the terminals 2 is an example of a“transmission station”. Note that the terminal 2 can serve as areceiving station, and the base station 1 can serve as a transmissionstation in some cases.

According to the embodiment, in multi-user MIMO, the terminals 2 cancommunicate using CG, and a state where the number of reception antennasM of the base station 1 is exceeded by the number N of terminals 2,i.e., a wireless communication system causing overloaded MIMO, isexemplified. The overloaded MIMO can be regarded as a state where thereceiving station receives signals arriving from transmission stationsthe number of which exceeds the number of reception antennas of thereceiving station. Note that the capability of data transmission by theterminal 2 through use of CG is not compulsory.

The terminal 2 is called a wireless communication terminal or a wirelessterminal. For example, the terminal 2 is used to collect data for IoT,and transmit the collected data to the base station 1. However, theusage of the terminal 2 is not limited.

FIG. 2 is a diagram illustrating a hardware configuration example of thebase station 1. In FIG. 2 , the base station 1 includes a processor 11,a memory device 12, an internal interface (internal IF) 13, a networkinterface (network IF) 14, and a wireless processing device 15.

The processor 11 is, for example, a central processing unit (CPU) (alsocalled a microprocessor unit (MPU)). The processor 11 may have asingle-processor configuration, or a multi-processor configuration. Asingle physical CPU connected by a single socket may have a multi-coreconfiguration. The processor 11 may include an operation device havingany of various circuit configurations, such as of a digital signalprocessor (DSP) or graphics processing unit (GPU). The processor 11 mayhave a configuration that cooperates with at least one of an integralcircuit (IC) and other digital circuits, and analog circuits. Theintegrated circuit encompasses an LSI, an application specificintegrated circuit (ASIC), and a programmable logic device (PLD). ThePLD encompasses, for example, a field-programmable gate array (FPGA).For example, the processor 11 may be what is called a micro controller(MCU), SoC (system-on-a-chip), a system LSI, or a chip set. Theprocessor 11 is an example of a control device or a controller.

The memory device 12 is used as a deployment area for a string ofinstructions (computer program) to be executed by the processor 11, amemory area for programs and data, a working area for the processor 11,and a buffer area for communication data. The memory device 12 is one ofexamples of a non-transitory storage medium.

The memory device 12 includes a main memory (called a memory), and anauxiliary memory. The main memory includes a random access memory (RAM),or a RAM, and a read only memory (ROM). The auxiliary memory encompassesa random access memory (RAM), a hard disk (HDD), a solid state drive(SSD), a flash memory, and an electrically erasable programmableread-only memory (EEPROM). Note that the type of the memory device 12 isnot limited to what is described above.

The processor 11 executes a program stored in the memory 12, therebyoperating as a device also called a base band unit (BBU). The BBUperforms a process of encoding and modulating data and generating abaseband signal, and an inverse process thereof (a process of convertingthe baseband signal into data by demodulating and decoding the basebandsignal). The base band unit can also be called a control unit.

The internal IF 13 is a circuit that connects various peripheral devicesto the processor 11. The network IF 14 is a communication device(circuit) for allowing the base station 1 to access a network to whichother base stations (base stations other than the base station 1) areconnected. The network to which base stations other than the basestation 1 are connected is also called a backhaul. The backhaul is, forexample, a wired network through optical communication.

The wireless processing device 15 includes a transceiver and a receiver.The transceiver and the receiver are connected to transceiving antennasANT-B1, . . . , ANT-BM via duplexers. Note that the bidirectionality ofthe antenna for transmission and reception is not compulsory. When theantennas ANT-B1, . . . , ANT-BM are not discriminated from each other,the antennas are represented as antennas ANT.

The transceiver includes a circuit that converts the baseband signal(digital signal) into an analog signal, a circuit that converts theanalog signal into a wireless signal, and a power amplifier thatamplifies the wireless signal. The receiver includes a low-noiseamplifier that applies low-noise amplification to the wireless signal, acircuit that converts the wireless signal into the analog signal, and acircuit that converts the analog signal into the digital signal(baseband signal). The wireless processing device 15 may adopt aconfiguration that includes N series of transceivers and receivers thenumber of which is equal to the number of antennas ANT.

The wireless processing device 15 performs conversion between thebaseband signal and the wireless signal, and an inverse process thereof.Accordingly, this device is also called a wireless device, or a wirelesscircuit. The wireless processing device 15 may have a configurationwhere the base band unit (BBU) is connected to a wired network throughoptical communication, and is installed at a remote place. In this case,the wireless processing device 15 is called a remote radio head (RRH).Alternatively, a configuration where multiple remote radio heads areconnected to one base band unit may be adopted. Note that the networkthat connects the base band unit and the remote radio heads to eachother is also called a fronthaul.

FIG. 3 is a diagram illustrating a configuration example of the terminal2. In FIG. 3 , together with the configuration of the terminal 2,wireless resource blocks are exemplified. The wireless resource blocksare parts divided by the frequency of the subcarrier allocated to theterminal 2, and the temporal axis. The wireless resource blocks forcommunication using CG have already been known by the terminals 2. Evenwithout allocation of the wireless resource blocks by the base station1, the terminals 2 can transmit data using the resource blocks for CG.

In FIG. 3 , the multiple terminals 2 (2-1, . . . , 2-N) are exemplified.The detailed configuration of each terminal 2 is illustrated in theterminal 2-1. In the example illustrated in FIG. 3 , each terminal 2includes two (a pair of) antennas. For example, the terminal 2-1includes antennas T-1 and T-2. The terminal 2-N includes antennas T-2N-1and T-2N. In the following description, when the antennas included inthe terminals 2-1 to 2-N are indicated without discrimination, theantennas are represented as “antenna(s) T”. Note that the number ofantennas T included in the terminal 2 is not limited to two.

The terminal 2 is sometimes called user equipment (UE). The terminal 2includes a processor, a memory, an internal IF and a wireless processingdevice that are similar to the processor 11, the memory device 12, theinternal IF 13 and the wireless processing device 15 that the basestation 1 includes. The wireless processing device is connected to theantenna T. The processor of the terminal 2 executes the program storedin the memory device, thereby allowing the terminal 2 to serve as anencoder 206, a modulator 207 and a transmission diversity processor 208in the wireless communication.

The encoder 206 applies error correction coding to data (transmissiondata) transmitted from the terminal 2. The error correction code may bea soft-decision code or a hard-decision code. There is no limitation tothe type of encoding. The modulator 207 digitally modulates theerror-correction-coded data. The scheme of digital modulation may be,for example, any of quadrature amplitude modulation (QAM), phase shiftkeying (PSK), frequency shift keying (FSK) and the like.

The transmission diversity processor 208 separates the digitallymodulated signal to multiple signals, and forms transmission diversitybranches. The transmission diversity processor 208 emits the signalsseparated to multiple branches, from the antennas T through the wirelessprocessing device. In the example of FIG. 3 , the transmission diversityprocessor 208 of each terminal 2 separates the transmission path by twoantennas, and forms transmission diversity branches.

A reference signal (RS) is added to each of the separated signals. TheRS is generally called a pilot signal, and is a signal having alreadybeen known by the base station 1. RSs different on aterminal-by-terminal basis are transmitted, thereby allowing the basestation 2 to identify the source terminals 2 by referring to the RSs.Note that the terminal 2 performs transmission diversity through thetransmission diversity processor 208. However, the transmissiondiversity is not compulsory. For example, a configuration may be adoptedwhere the terminal 2 uses one antenna for transmission and does notperform transmission diversity. The number of series of signalsseparated by the transmission diversity may be two or more depending onthe number of antennas.

FIG. 4 illustrates a configuration example of the base station 1. Theprocessor 11 executes the program stored in the memory device 12,thereby allowing the base station 1 to operate as an apparatus thatperforms processes illustrated in FIG. 4 . That is, the base station 1operates as the apparatus that includes a replica remover 101, adiversity reception and equalization unit 102, a demodulator 103, adecoder 104, and a replica generator 105. The replica generator 105operates as a device that includes an encoder 106, a modulator 107, atransmission diversity processor 108, and a channel matrix multiplier109.

In the base station 1, RSs are extracted from the respective signalsreceived from the M antennas ANT (ANT-B1 to ANT-BM). The RS is used toidentify the terminal 2, and to estimate the channel for the signal fromthe terminal 2. The reception diversity and equalization unit 102performs reception diversity and equalization using the minimum meansquare error (MMSE).

That is, the reception diversity and equalization unit 102 generates achannel matrix from channel estimation values using the RS of a desiredsignal, and calculates an MMSE weight for suppressing interference fromother transmission antenna branches with respect to each correspondingtransmission antenna branch. Furthermore, the reception diversity andequalization unit 102 multiplies the reception signal vector by the MMSEweight matrix, thereby obtaining an equalized signal with interferencebeing suppressed.

The demodulator 103 calculates the log-likelihood ratio (LLR), on abit-by-bit basis, from the squared Euclidean distance between theequalized signal and a transmission signal point replica. The decoder104 performs error correction decoding using LLR, and decodes the data.

The replica generator 105 performs a process of generating a replica ofthe desired signal, from data obtained by the decoder 104. That is, thereplica generator 105 generates the replica of the desired signalthrough the encoder 106, the modulator 107, the transmission diversityprocessor 108, and the channel matrix multiplier 109. The replicaremover 101 removes the desired signal from the signal received by thebase station 1 using the replica. This is called an SIC (successiveinterference canceller) loop. A successfully demodulated and decodedsignal (an interference replica of the transmission signal) is removedfrom the incoming signal (reception signal), thereby allowing theinterference signal with respect to the desired signal to be reduced.According to this embodiment, the desired signals are selected in adescending order of the signal-to-interference ratio (SIR) from amongsignals received by the base station 1 from N terminals 2. Note that theselection order of the desired signals may be according to that otherthan the SIR order.

FIGS. 5 and 6 illustrate an overloaded MIMO state. According to theoverloaded MIMO, signals from terminals 2 the number of which is largerthan the number of reception antennas M of the base station 1 havearrived. The channel matrix H in this case can be represented by thefollowing expression (1).

[Expression1] $\begin{matrix}{H = {\left\lbrack {H_{c},H_{u}} \right\rbrack = \begin{pmatrix}h_{1,1} & h_{1,2} & \ldots & h_{1,N} \\h_{2,1} & h_{2,2} & \ldots & h_{2,N} \\ \vdots & \vdots & \ddots & \vdots \\h_{M,1} & h_{M,2} & \ldots & h_{M,N}\end{pmatrix}}} & (1)\end{matrix}$

The channel matrix H is a matrix indicating the variation amounts ofamplitudes and phases of transmission paths between the antennas T1 toTN of the terminals 2 and the antennas ANT-B1 to ANT-BM of the basestation 1. The channel matrix H is determined by receiving the RSstransmitted from the antennas 2 j-1, 2 j (j=1, . . . , N) of theterminals 2 through the antennas ANT-B1 to ANT-BM. This similarlyapplies to cases where the number of antennas of each terminal 2 isdifferent from two. In brief, the variation amount corresponding to thetransfer function of the transmission path can be obtained depending onthe reference signal transmitted and received between thetransmission-side antennas 2 j-1 and 2 j and the reception-side antennaANT-Bi. h_(m,n) in the channel matrix H indicates the channel estimationvalue about what is transmitted from the n-th terminal among theterminals 2, and received by the m-th antenna ATN in the base station 1.

The channel matrix H is a matrix indicating the variation amounts ofamplitudes and phases of transmission paths between the antennas T ofthe terminals 2 and the reception antennas ANT-B1 to ANT-BM of the basestation 1. The transmission signal vector of each antenna T of theterminal 2 is multiplied by the channel matrix H, which can obtain theestimation values of the reception signal vectors at the receptionantennas ANT-B1 to ANT-BM of the base station.

According to this embodiment, the RSs are orthogonal so as not tointerfere with each other between the terminals 2. Since the RSs areorthogonal, the base station 1 can estimate the channel matrix H fromthe RSs even in an overloaded MIMO state.

In the overloaded MIMO, the number N of terminals 2 exceeds the numberof reception antennas M. Any of the signals of the terminals the numberof which is N (e.g., the signal of the terminal 2-1) is assumed as thedesired signal (indicated by thick arrows in FIGS. 5 and 6 ). In thiscase, the signals of M−1 parts (the signals of the terminals 2-2 to 2-M)are signals that are suppressed (cancelled) according to an MMSE method(indicated by broken arrows in FIGS. 5 and 6 ). The signals of N-M parts(the signals of the terminals 2-M+1 to 2-N) are signals that are notsuppressed (cancelled) according to the MMSE method (indicated bychain-line arrows in FIGS. 5 and 6 ).

Accordingly, the channel matrix H includes a transmission path vectorH_(c), and a transmission path vector H_(u). The transmission pathvector H_(c) is a transmission path vector (channel matrix) thatincludes the transmission path vector h₁ of the desired signal, and thetransmission path vector (channel matrix) H′_(c) of the signals to becancelled. The transmission path vector H_(u) is the transmission pathvector (channel matrix) of the signal not to be cancelled. The matrix ofthe transmission path vector H_(c) is represented by the followingexpression (2). The transmission path vector of the desired signal h₁ isrepresented by an expression (3). The transmission path vector H′_(c) isrepresented by the following expression (4).

[Expression2] $\begin{matrix}{H_{c} = \begin{pmatrix}h_{1,1} & h_{1,2} & \ldots & h_{1,M} \\h_{2,1} & h_{2,2} & \ldots & h_{2,M} \\ \vdots & \vdots & \ddots & \vdots \\h_{M,1} & h_{M,2} & \ldots & h_{M,M}\end{pmatrix}} & (2)\end{matrix}$ $\begin{matrix}{h_{1} = \left( {h_{1,1},h_{2,1},\ldots,h_{M,1}} \right)^{T}} & (3)\end{matrix}$ $\begin{matrix}{H_{c}^{\prime} = \begin{pmatrix}h_{1,2} & h_{1,3} & \ldots & h_{1,M} \\h_{2,2} & h_{2,3} & \ldots & h_{2,M} \\ \vdots & \vdots & \ddots & \vdots \\h_{M,2} & h_{M,3} & \ldots & h_{M,M}\end{pmatrix}} & (4)\end{matrix}$

The transmission path vector (channel matrix) H_(u) not to be cancelledis represented by the following expression (5).

[Expression3] $\begin{matrix}{H_{u} = \begin{pmatrix}h_{1,{M + 1}} & h_{1,{M + 2}} & \ldots & h_{1,N} \\h_{2,{M + 1}} & h_{2,{M + 2}} & \ldots & h_{2,N} \\ \vdots & \vdots & \ddots & \vdots \\h_{M,{M + 1}} & h_{M,{M + 2}} & \ldots & h_{M,N}\end{pmatrix}} & (5)\end{matrix}$

According to the typical MMSE method, the MMSE weight that suppresses(cancels), as the interference signal, the signal of “M−1” parts thenumber of which is obtained by subtracting one from the number ofreception antennas M. However, according to the overloaded MIMO, thesignal of “N-M” parts the number of which is obtained by subtracting thenumber M of antennas from the number N of terminals 2 is not suppressed(cancelled).

Consequently, there is a possibility of increase in the error rateduring demodulation according to the MMSE equalization through thetypical MMSE method.

According to this embodiment, the reception diversity and equalizationunit 102 calculates the weight (MMSE weight W_(mnse)) in considerationof the interference signal (the signal of N-M parts) uncanceled in theoverloaded MIMO state. By this calculation, increase in the error rateduring demodulation is suppressed.

FIG. 7 is a flowchart illustrating an example of a weight calculationprocess in MMSE diversity, the process being executed by the receptiondiversity and equalization unit 102 (the processor 11 operating as thisunit). FIG. 8 illustrates definition of symbols and the like used forweight calculation indicated in FIG. 7 .

In step S21, the processor calculates a weight W_(zf) for removing theinterference signal (the signal of “M−1” parts) to be cancelled byreception diversity using the zero forcing method (ZF method). Theexpression of calculating the weight W_(zf) is indicated in the block ofstep S21. Here, R_(c) indicates the transmission path vector multipliedby the transmission amplitude p of the desired signal and the signal tobe cancelled, and r₁ indicates the transmission path vector multipliedby the transmission amplitude p of the desired signal. The symbol “T”indicates the transposed matrix, and the symbol “*” indicates thecomplex conjugate. By the following expression (6), r₁ can berepresented. R_(c) can be represented by the following expression (7).Note that as the first desired signal, for example, the signal havingthe highest SIR is selected from among the signals of the terminals 2identifiable by RS. Note that the order of selecting the desired signalis not limited to the descending order of SIR.

[Expression4] $\begin{matrix}{r_{1} = {{p_{1}h_{1}} = \left( {p_{1}h_{1,1},p_{1}h_{2,1},\ \ldots,p_{1}h_{M,1}} \right)^{T}}} & (6)\end{matrix}$ $\begin{matrix}{R_{c} = {\left\lbrack {{p_{1}h_{1},p_{2}h_{2}},{\ldots,p_{M}h_{M}}} \right\rbrack = \begin{pmatrix}{p_{1}h_{1,1}} & {p_{2}h_{1,2}} & \ldots & {p_{M}h_{1,M}} \\{p_{1}h_{2,1}} & {p_{2}h_{2,2}} & \ldots & {p_{M}h_{2,M}} \\ \vdots & \vdots & \ddots & \vdots \\{p_{1}h_{M,1}} & {p_{2}h_{M,2}} & \ldots & {p_{M}h_{M,M}}\end{pmatrix}}} & (7)\end{matrix}$

In step S22, the processor 11 calculates the weight W′_(zf) obtained bynormalizing the weight W_(zf). The calculation expression ofnormalization is as illustrated in the block of step S22. In step S23,the processor 11 calculates the interference signal vector G_(u)obtained by multiplying R_(u) by the weight W_(zf). The calculationexpression of G_(u) is as illustrated in the block of step S23. R_(u) isa channel matrix obtained by multiplying the signal (the interferencesignal of “N-M” parts) that is uncanceled through the receptiondiversity, by the transmission amplitude p, and can be represented bythe following expression (8).

[Expression5] $\begin{matrix}{R_{u} = {\left\lbrack {p_{M + 1}h_{M + 1},p_{M + 2}h_{{M = 2},\ldots,{p_{N}h_{N}}}} \right\rbrack = \begin{pmatrix}{p_{M + 1}h_{1,{M + 1}}} & {p_{M + 2}h_{1,{M + 2}}} & \ldots & {p_{N}h_{1,N}} \\{p_{M + 1}h_{2,{M + 1}}} & {p_{M + 2}h_{2,{M + 2}}} & \ldots & {p_{N}h_{2,N}} \\ \vdots & \vdots & \ddots & \vdots \\{p_{M + 1}h_{M,{M + 1}}} & {p_{M + 2}h_{M,{M + 2}}} & \ldots & {p_{N}h_{M,N}}\end{pmatrix}}} & (8)\end{matrix}$

In step S24, the processor 11 calculates the summation of the power(interference power) P_(u) of the interference signal vectors G_(u). Thecalculation expression of P_(u) is as illustrated in the block of stepS24. P_(u) is the power of the signals of the terminals 2-M+1 to 2-Nillustrated in FIG. 6 that are not cancelled, i.e., the sum of p_(m+1)², . . . , p_(N) ². The power per terminal is calculated as one in thecalculation expression.

In step S25, the processor 11 calculates the weight W_(mmse) inconsideration of the amount of interference by the MMSE method. Thecalculation expression of W_(mmse) is as illustrated in the block ofstep S25. The typical weight calculation expression considers P_(n),i.e., the noise power per reception antenna. Meanwhile, according tothis embodiment, in addition to P_(n), the power P_(u) of (the part, bywhich the number N of terminals 2 exceeds the number of receptionantennas M, of) the interference signal that is not cancelled by thereception diversity is considered. Consequently, the signal of theterminals 2 concerned can be suppressed as the interference signal.

According to the calculation expression of the MMSE weight W_(mmse)illustrated in the block of step S25, the value of W_(mmse) depends onthe power P_(u) of N-M terminals 2. Consequently, in step S26, theprocessor 11 sets the current value of W_(mmse) to the value of W_(zf),and the processing returns to step S22. Accordingly, in step S22 to S25,the new value of W_(mmse) is calculated (updated). According to thisembodiment, the value of W_(mmse) calculated at the second time is usedfor multiplication of suppression of the interference signal.

Subsequently, by the replica generator 105 and the replica remover 102,the desired signal h₁ is removed from the incoming signal using areplica of the desired signal h₁. The next desired signal h₂ is thenselected; for this desired signal h₂, the interference signal issuppressed using the weight W_(mmse) calculated by the processillustrated in FIG. 7 . The process according to such an SIC loop isrepeated. Note that in the situation where MIMO is not overloaded, i.e.,where the number N of terminals 2 is equal to or less than the number ofreception antennas M, there is no R_(u). Accordingly, the power P_(u) isnot calculated, and weight calculation according to the typical MMSEmethod is performed.

Note that in the process illustrated in FIG. 7 , W_(zf) is used toobtain the initial value of the power P_(u). Alternatively, thecalculation result of the calculation expression (W=(R_(c)*R_(c)^(T)+(P_(n))I)⁻¹r₁*) of the typical MMSE weight may be used instead ofWzf.

FIGS. 9 to 11 exemplify simulation results according to the process ofthis embodiment. FIG. 9 exemplifies the condition of the simulation. Thesimulation is performed for a case where the number of simultaneoustransmission terminals is 3 to 6 (two transmission antennas in eachterminal 2), and a case where the number of simultaneous transmissionterminals is 5 to 10 (four transmission antennas in each terminal 2).

The transmission data size is 80 bits. The error correction code is aturbo code (code rate of 1/3). The modulation scheme is the singlecarrier QPSK. It is assumed that the transmission path is single-pathRayleigh fading with the maximum Doppler frequency of 0 Hz. It isfurther assumed that the signal-to-noise power ratio (SIR) of thetransmission path is 30 dB.

FIG. 10 exemplifies the difference of the first SIC bit error rate in acase of using a typical MMSE weight calculation method in thesimulation, and a case of using the MMSE weight calculation method ofthis embodiment (according to this proposal). The example illustrated inFIG. 10 illustrates a case where the number of reception antennas of thereceiving station (base station) is two and the number of terminals isthree (the number of terminals exceeding the number of receptionantennas is one (N−M=1)). Each graph in FIG. 10 is an example withouttransmission diversity. In FIG. 10 , the abscissa axis indicates SIR(dB), and the ordinate axis indicates the bit error rate. In FIG. 10 ,the upper graph indicates a case of using the typical MMSE weightcalculation method, and the lower graph indicates a case of using theMMSE weight calculation method according to this proposal. The exampleillustrated in FIG. 11 indicates a case where the number of receptionantennas is four and the number of terminals is five (the number ofterminals exceeding the number of reception antennas is one).

As illustrated in FIGS. 10 and 11 , it is understood that application ofthe MMSE weight calculation method according to this proposal indicatesa more favorable bit error rate irrespective of the value of SIR. Thatis, the calculation method according to this proposal can suppress theinterference and suppresses the bit error rate more than the typicalMMSE weight calculation method.

As described above, according to the wireless communication system(wireless communication control method) in the embodiment, in a case ofintending to suppress interference by the MMSE diversity in theoverloaded MIMO, the power P_(u) of the signals of the terminals 2corresponding to the parts (M-N parts) by which the number of terminalsN exceeds the number of reception antennas M (step S24). The power P_(u)is the sum of square norms of the interference signal vectors G_(u)corresponding to N-M parts. The MMSE weight W_(mmse) depending on thepower P_(u) is calculated (step S25).

According to this embodiment, to obtain the initial value of the powerof P_(u) of the interference signal, the initial value of the MMSEweight is set. The initial value of the MMSE weight can be obtained bycalculating the weight W_(zf) by the zero forcing method using a matrixR_(e) (step S21). The matrix R_(e) is a matrix obtained by multiplyingthe channel matrix H_(e) of these terminals 2 by the transmissionamplitude p of the signals of the terminal 2 corresponding to thetransmission terminals of the desired signals and the parts the numberof which is (M−1) that is the number smaller by one than the number ofreception antennas M. Note that the initial value of the weight may beobtained by the MMSE weight calculation method (typical MMSE weightcalculation method) for the transmission terminal of the desired signal(first SIC desired signal) and the parts the number of which is (M−1)that is the number smaller by one than the number of reception antennasM.

When the MMSE weight W_(mmse) depending on the power P_(u) using theinitial value of the power P_(u) (step S25), the value is set as theinitial value of the MMSE weight (step S26), and the power P_(u) isrecalculated (step S24). Accordingly, a more appropriate weight W_(mmse)is calculated, and the channel matrix is multiplied by the weight.Accordingly, the interference in the overloaded MIMO can beappropriately suppressed, and the error rate during demodulation can besuppressed (see FIGS. 10 and 11 ).

The calculated value of P_(u) can be used to calculate thelog-likelihood ratio (LLR) used to demodulate the error correction codeduring demodulation, and the error rate after error correction can bereduced in comparison with a case without using P_(u).

In this embodiment, according to the SIC method, the signal with thehighest SIR among the signals of the N terminals is identified as thefirst desired signal. The MMSE equalization result for the desiredsignal is output from the reception diversity and equalization unit 102,and used for demodulation and decoding. A replica of the first desiredsignal is generated, and the first desired signal is removed from Nincoming signals, using the replica. The calculation of the MMSE weightaccording to this embodiment is applicable to all the second desiredsignals and thereafter.

Note that the method of calculating the MMSE weight according to thisembodiment is also applicable to the typical MMSE method other than theSIC method, i.e., a case where MMSE equalization results for individualtransmission signals are calculated in parallel. The factor ofoccurrence of the overloaded MIMO is not limited to use of CG. Even whenthe number of terminals N of signals from one terminal (transmissionstation) exceeds the number of reception antennas M in the receivingstation, the MMSE weight calculation method according to this embodimentis applicable. The configuration of the embodiment is an example. Theconfiguration described in the embodiment can be appropriately changedin a range without departing from the spirit of the present disclosure.

1. A wireless communication control method suppressing interferenceusing a minimum mean square error (MMSE) weight in an environment ofwireless communication where the number of transmission stationstransmitting a wireless signal to a receiving station is larger than thenumber of reception antennas of the receiving station, the methodcomprising: calculating, by the receiving station, power of aninterference signal included in a signal received by the receivingstation from the transmission stations the number of which is largerthan the number of reception antennas, the interference signalcorresponding to a part by which the number of transmission stationsexceeds the number of reception antennas; calculating, by the receivingstation, an MMSE weight depending on the power of the interferencesignal; and performing, by the receiving station, MMSE diversity usingan MMSE weight obtained by recalculating the power of the interferencesignal using the MMSE weight depending on the power of the interferencesignal and recalculating the MMSE weight depending on the recalculatedpower of the interference signal.
 2. The wireless communication controlmethod according to claim 1, wherein in calculation of the power of theinterference signal, an initial value of the power of the interferencesignal is calculated by multiplying, by an initial value of the MMSEweight, a channel matrix of the interference signal multiplied by atransmission amplitude.
 3. The wireless communication control methodaccording to claim 2, wherein in the calculation of the power of theinterference signal, the initial value (W_(zf)) of the MMSE weight iscalculated by the receiving station using a zero forcing method.
 4. Areceiving station comprising a plurality of reception antennas andconfigured to suppress interference using a minimum mean square error(MMSE) weight in an environment where the number of transmissionstations transmitting a wireless signal is larger than the number of theplurality of reception antennas, the receiving station comprising acontroller configured to execute: calculating power of an interferencesignal included in a signal received by the receiving station from thetransmission stations the number of which is larger than the number ofreception antennas, the interference signal corresponding to a part bywhich the number of transmission stations exceeds the number ofreception antennas; calculating an MMSE weight depending on the power ofthe interference signal; performing, by the receiving station, MMSEdiversity using an MMSE weight obtained by recalculating the power ofthe interference signal using the MMSE weight depending on the power ofthe interference signal and recalculating the MMSE weight depending onthe recalculated power of the interference signal.
 5. The receivingstation according to claim 4, wherein in calculation of the power of theinterference signal, the controller calculates an initial value of thepower of the interference signal by multiplying, by an initial value ofthe MMSE weight, a channel matrix of the interference signal multipliedby a transmission amplitude.
 6. The receiving station according to claim5, wherein in the calculation of the power of the interference signal,the controller calculates the initial value of the MMSE weight using azero forcing method.
 7. A non-transitory storage medium storing aprogram causing computer of a receiving station comprising a pluralityof reception antennas and configured to suppress interference using aminimum mean square error (MMSE) weight in an environment where thenumber of transmission stations transmitting a wireless signal exceedsthe number of the plurality of reception antennas, the program causingthe computer to execute: calculating power of an interference signalincluded in a signal received by the receiving station from thetransmission stations the number of which is larger than the number ofreception antennas, the interference signal corresponding to a part bywhich the number of transmission stations exceeds the number ofreception antennas; calculating an MMSE weight depending on the power ofthe interference signal; and performing, by the receiving station, MMSEdiversity using an MMSE weight obtained by recalculating the power ofthe interference signal using the MMSE weight depending on the power ofthe interference signal and recalculating the MMSE weight depending onthe recalculated power of the interference signal.
 8. The non-transitorystorage medium according to claim 7, wherein the program causes thecomputer to execute a process, in calculation of the power of theinterference signal, of calculating an initial value of the power of theinterference signal by multiplying, by an initial value (W′_(zf)) of theMMSE weight, a channel matrix of the interference signal multiplied by atransmission amplitude.
 9. The non-transitory storage medium accordingto claim 8, wherein the program causes the computer to execute aprocess, in the calculation of the power of the interference signal, ofcalculating the initial value (W_(zf)) of the MMSE weight using a zeroforcing method.